文献
J-GLOBAL ID:201702224495748938
整理番号:17A0776415
最適化のために高速変換する一貫した教育-学習-自己学習アルゴリズム:微粉炭を隅角燃焼するボイラからのNOx排出予測のためのLSSVMパラメータ調整の事例検討
A Fast Converging and Consistent Teaching-Learning-Self-Study Algorithm for Optimization: A Case Study of Tuning of LSSVM Parameters for the Prediction of NOx Emissions from a Tangentially Fired Pulverized Coal Boiler
著者 (6件):
Ahmed Faisal
(Department of Chemical Engineering, Hanyang University)
,
Ahmed Faisal
(Department of Chemical Engineering, COMSATS Institute of Information Technology)
,
Kim Jin-Kuk
(Department of Chemical Engineering, Hanyang University)
,
Khan Asad Ullah
(Department of Chemical Engineering, COMSATS Institute of Information Technology)
,
Park Ho Young
(KEPRI)
,
Yeo Yeong Koo
(Department of Chemical Engineering, Hanyang University)
資料名:
Journal of Chemical Engineering of Japan
(Journal of Chemical Engineering of Japan)
巻:
50
号:
4
ページ:
273-290(J-STAGE)
発行年:
2017年
JST資料番号:
S0629A
ISSN:
0021-9592
CODEN:
JCEJAQ
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
日本 (JPN)
言語:
英語 (EN)